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This chapter is from the book

7.2 The Sample Application

Our sample application will be an order entry application. We chose an order entry application as the sample for this chapter for two main reasons. The first is to make it a nontrivial, business-oriented application, one that would demonstrate LINQ's ability to manipulate both ADO.NET data objects and business objects to easily perform commonly required tasks.

The second reason for making it an order entry application is that a familiar source of data is already available: the Northwind database. The Northwind database has been around for a long time now, and its structure is familiar to many, so much so that we have already used it in previous examples. What is important is not whether our application is an order entry application but whether it illustrates ways to use LINQ in your application and the benefits of doing so.

Our application will use five Northwind tables, as shown in Table 7.1. To eliminate much repetition of code and text, we will use a small number of columns from each table, just enough to illustrate the things that a typical smart-device application would need to do, and we will use LINQ to do as many of those things as possible.

Table 7.1. Five Northwind Tables Used by the LINQ Sample Application

Northwind Table

Employees

Customers

Products

Orders

Order Details

From a business perspective, the application allows any employee to sell any product to any customer. The employee uses the application to

  1. Retrieve all of the employee's orders from the host SQL Server
  2. Add, delete, and modify orders
  3. Save/restore all application data to a local file
  4. Upload all entered information to the host SQL Server

From a developer's perspective, the application will

  1. Use ADO.NET classes to retrieve data from a SQL Server database
  2. Store that data in a data set (the LINQ to Datasets version) or in business objects of our own design (the LINQ to Objects version) or in a combination of both (the hybrid version)
  3. Bind our data to controls
  4. Validate data
  5. Use XML serialization to move application data to and from the device's object store
  6. Upload changes to the SQL Server database

Figure 7.1 shows a schematic diagram of the application.

Figure 7.1

Figure 7.1 Sample Application Schematic Diagram

The entire code of the application is not shown in this book, as doing so would take too much space. If you've seen one regular expression used to validate one string property, you've seen one used to validate them all. If you've seen one business object track changes, you've seen them all track changes. Rather than show all the code, we will focus on one or two classes, and on the utility routines that are used to provide functionality to all objects, and especially on the use of LINQ within that code. You can find the complete code for all three versions of the application at the book's website. Each version has its own project subdirectory: LinqToDatasets, LinqToObjects, and LinqHybrid.

The main starting point for the application is the retrieval of the employee's orders from the Northwind database. The employee's row must be retrieved from the Employees table, the employee's orders retrieved from the Orders table, and their details retrieved from the Order Details table. Since an employee can sell any product to any customer, all rows must be retrieved from both the Customers and the Products tables. This information is gathered by a SQL Server stored procedure that takes the employee ID as its only parameter and retrieves the necessary rows from each table. Listing 7.3 shows this procedure.

Listing 7.3. SQL Server Stored Procedure for Accessing Employee's Order Records

ALTER PROCEDURE dbo.procGetEmployee
      @EmployeeID int
AS
BEGIN
   SET NOCOUNT ON;

   SELECT *
     FROM dbo.Employees
     WHERE EmployeeID = @EmployeeID

   SELECT *
     FROM dbo.Customers

   SELECT *
     FROM dbo.Products

   SELECT *
     FROM dbo.Orders
     WHERE EmployeeID = @EmployeeID

   SELECT *
     FROM dbo.[Order Details]
     WHERE OrderID IN
        ( SELECT OrderID
            FROM dbo.Orders
           WHERE EmployeeID = @EmployeeID )
END
GO

The information retrieved by this stored procedure, when brought into the application's memory space, results in the application data structure that is diagrammed in Figure 7.2. Throughout this chapter, we will refer to this data as the application data, regardless of whether it is stored in data tables within a data set or in collections of business objects contained within a parent XML-serializable object.

Figure 7.2

Figure 7.2 The Application's Data

Within the application, the data that was retrieved from the [Order Details] table will be known by the one-word name, Details. The authors of this book have strong, and not positive, opinions regarding the use of spaces within object names.

Now that we have the server-side stored procedure in place, we turn our attention to the client-side application and the code needed to receive and process the data. We start with the LINQ to Datasets version. Since we'll be using LINQ to Datasets, we can make our schematic diagram a bit more specific, as shown in Figure 7.3.

Figure 7.3

Figure 7.3 Sample Application Diagram: LINQ to Datasets

7.2.1 LINQ to Datasets

As we did in Chapter 6, ADO.NET Programming, we'll use a DataAdapter object to receive the data from the stored procedure and place it in a data set. But this time we have five SELECT statements in our stored procedure. Therefore, our adapter will need to generate five tables in our data set and load each with the results from a different SELECT statement. Before executing the adapter's Fill method, we will need to tell the adapter what name to give each table in the data set. We do not need to tell the adapter what data source tables were used, as the adapter knows each incoming result set within the output of a multi SELECT command by the names Table, Table1, Table2, and so on, regardless of the underlying database table names.

We match the name that we want the adapter to give each data table to the incoming result sets—Table, Table1, Table2, and so on—by adding entries to the adapter's TableMappings collection. In our case, five entries are required, as shown in the following code snippet:

dapt.TableMappings.Add("Table", "Employees");
dapt.TableMappings.Add("Table1", "Customers");
dapt.TableMappings.Add("Table2", "Products");
dapt.TableMappings.Add("Table3", "Orders");
dapt.TableMappings.Add("Table4", "Details");

Listing 7.4 provides the complete code necessary to accomplish the following four tasks.

Listing 7.4. Client-Side Code to Load a Multitable Data Set

DataSet dsetEmployee = new DataSet();
SqlDataAdapter dapt;

SqlConnection conn =
   new SqlConnection(connectionString);
SqlCommand cmnd = conn.CreateCommand();
cmnd.Parameters.AddWithValue("@Return", 0);
cmnd.Parameters[0].Direction =
   ParameterDirection.ReturnValue;

dapt = new SqlDataAdapter(cmnd);

dapt.SelectCommand.CommandType =
                     CommandType.StoredProcedure;
dapt.SelectCommand.CommandText =
                     "dbo.procGetEmployee";
dapt.SelectCommand.Parameters
         .AddWithValue("@EmployeeID", employeeID);
dapt.TableMappings.Add("Table", "Employees");
dapt.TableMappings.Add("Table1", "Customers");
dapt.TableMappings.Add("Table2", "Products");
dapt.TableMappings.Add("Table3", "Orders");
dapt.TableMappings.Add("Table4", "Details");

dapt.Fill(dsetEmployee);
  1. Create an empty Dataset.
  2. Create the connection, command, and adapter objects.
  3. Set the TableMappings collection.
  4. Retrieve the data and load it into the data set.

The connectionString and employeeID are passed into the function containing the code. The resulting DataSet has the structure shown in Figure 7.4 and is the application data object for this version of the application. To make all three versions of our application as consistent as possible, we will always place a reference to the application data object into a static field named AppData located in the Program class. In this version, the data set is the application data object.

Figure 7.4

Figure 7.4 Structure of Data Set

The code shown in Listing 7.4 does not contain any LINQ statements, for it just loads data from a remote database into a data set on the device. Only after we have placed the data into the data set will we begin to use LINQ to manipulate that data.

Once we have the data, we need to display it to the user. This is where the capabilities of LINQ begin to come in. For example, consider a form, FormEmployee, that lets an employee choose which order to work on. This form must display a drop-down list of orders within a ComboBox. Combo boxes need two pieces of information per item being listed: the value that will serve as the identifying key of the item and the text value to be displayed to the user.

Unfortunately, the Orders data table has no single column that we wish to display, for no single column contains all of the information we want the user to see. We want to display a composite of fields to the user. This is a common need. How many times has a developer needed to display a drop-down list listing people from a table that had a FirstName and LastName column but no FullName column—or in this case, the need to combine customer ID, order date, and net value into the list?

Thanks to LINQ—with the help of Visual Studio's IntelliSense—we write the code shown in Listing 7.5 to bind rows from the Orders data table to the combo box. The result appears in Figure 7.5.

Figure 7.5

Figure 7.5 Results from LINQ Query Displayed on Smart-Device Screen

Listing 7.5. Client-Side User Interface Code

cbxOrders.DisplayMember = "Text";
cbxOrders.ValueMember = "Id";
cbxOrders.DataSource =
(
   employee.Orders
      .OrderBy(order => order.parentCustomer.CompanyName)
         .ThenByDescending(order => order.NetValue)
         .ThenByDescending(order => order.OrderDate)
      .Select(sorted =>
         new
         {
            Id = sorted.OrderID,
            Text = sorted.parentCustomer.CustomerID
                 + " - "
                 + sorted.NetValue.ToString("c")
                           .PadLeft(9).Substring(0, 9)
                 + " - "
                 + sorted.OrderDate
                           .ToString("dd-MMM-yy")
         })
)
.ToList();

Again, we remind readers that an alternative syntax, the query expression syntax, was shown in Listing 7.2.

In the code, in one statement, we produced a sorted list of objects from a data table, objects of a class that did not exist when the statement began. We defined that class, a class containing Id and Text properties, within the statement itself. Every row in the data table was used to create an object of the new class and that object was placed into a new collection, which in turn was converted into a System.Collections.Generic.List object and bound to the combo box.

Like anything related to programming, the placement of parentheses is critical. Had the parenthesis that appeared just before ToList appeared after it, the statement would not have compiled. The steps involved in the creation of the new collection of new objects had to be specified in its entirety before that collection could be converted into a List.

Another point must be made regarding the ToList operator; namely that it exists in this LINQ statement to satisfy a DataSource need, not a LINQ need. That is, the Select operator generates a collection that implements IEnumerable. If an enumerable collection were all that we needed, ToList would not have been part of the statement. But a ComboBox Data-Source requires a collection that implements IList, not IEnumerable, thus the need for the final step of converting an enumeratable collection into a listable collection.

We also sorted the rows, not within the data table but for output. Some developers might say, "No big deal. Arrays and many collection classes have always been able to sort the objects contained within them." This is true, but there is a huge difference between that kind of sorting and LINQ sorting. Previous set sorting required that the determination of the fields to be used for the comparison be made by the objects being sorted or by a third, supporting, object and that those objects implement the IComparer or IComparable interface. In LINQ sorting, we specify the sort criteria in the statement itself; criteria that, as we mentioned earlier in the chapter, can be defined and modified at runtime.

Had we wanted to sort on the concatenated field that we generated within the execution of the statement, we would have done the sort after the select, as shown in the example code in Listing 7.6. In this example, the Text property of the on-the-fly defined class, the anonymous class as it is known, is used as the sort key.

Listing 7.6. Sorting Anonymous Objects

cbxOrders.DataSource =
(
   employee.Orders
      .Select(sorted =>
         new
         {
            Id = sorted.OrderID,
            Text = sorted.parentCustomer.CustomerID
                 + " - "
                 + sorted.NetValue.ToString("c")
                       .PadRight(9).Substring(0, 9)
                 + " - "
                 + sorted.OrderDate.ToString("dd-MMM-yy")
         })
      .OrderBy(item => item.Text))
   .ToList();

One comment about these anonymous classes that LINQ statements generate for you: They are truly anonymous. If you set a break point and drill down into the bound object, you'll see that objects within it are objects of a certain structure but not of any name. This means that no object of another class can be cast as an object of an anonymous type.

It also means that it is sometimes impossible to use LINQ's Union method with anonymous classes. Since Union can be used only to connect two sets of the same class, and since Union cannot base that determination on class name when anonymous classes are involved, it must examine the metadata of the two anonymous classes that are to be Unioned and ascertain that they match perfectly.

The authors have occasionally been surprised at what they could and could not Union. For instance, the form that is displayed before FormEmployee, FormStart, also has a combo box. It is used to display a list of employee IDs. Just to experiment, we decided to use a Union and to place an additional entry at the start of the list, an entry containing the following instruction to the user: "Select your Employee No". You must use Union in this scenario because you cannot add any entries to a combo box after it has been data-bound. You must merge the additional entries into the set before data binding. The code, which appears in Listing 7.7, works just fine, producing the result shown in Figure 7.6. When we tried to add the same user instruction to the top of the combo box in FormEmployee, using the same Union clause to do so, it failed. However, if we Unioned the user instruction to the end of this list, by swapping the two sides of the Union, the code succeeded.

Figure 7.6

Figure 7.6 Display of ed Lists

Listing 7.7. Unioning Two Lists

private List<string> topOfList =
   new List<string>
      (new string[1] { "<Select your Employee No>" });

private List<int> EmployeeIDs =
   new List<int>(
      new int[9] { 1, 2, 3, 4, 5, 6, 7, 8, 9 });

cbxEmployeeID.DisplayMember = "Text";
cbxEmployeeID.ValueMember = "Id";
cbxEmployeeID.DataSource =
(
   (
   topOfList
      .Select(instruction =>
         new
         {
            Id = 0,
            Text = instruction
         }))
   .Union
   (
   EmployeeIDs
      .Select(item =>
         new
         {
            Id = item,
            Text = item.ToString()
         }))
 )
 .ToList();

The moral of the story is that we should expect that one anonymous class would be different from another anonymous class and that any attempt to cast from one type to another, however implicit it may be, may fail regardless of how similar their definitions may appear.

As we just saw, in our LINQ to Datasets application, we use LINQ to extract data from our data set tables, transform it, and bind it to controls. Regarding the non-LINQ functionality of our application, the Dataset class was a great help. As we mentioned in Chapter 6, the data set allows us to persist application data to local storage through its ReadXML and WriteXML methods; and it assists us in delivering changes back to the remote database by providing the data adapter's Update method, a method that relies on the DataRow class's change tracking and primary key capabilities to build the necessary data modification statements.

What data sets do not provide is a central location for business logic. We cannot make the data set validate user input, for there is no way to tell a data set that "WA state driver's license numbers must be one letter, followed by six letters or *s, followed by three digits, followed by two letters" or "No one is allowed to have more than four books checked out of this lending library at a time."

Providing a central location for business logic is a job for business objects. Who better to validate customer ID than the Customer class itself? Who better to specify the calculation of an order's net value than the Order class? So, let us transition our application to use business objects, for doing so will provide us a with way to illustrate the use of LINQ to Objects.

7.2.2 LINQ to Objects

To cover LINQ to Objects, we will modify the sample application. The new version will

  1. Still use ADO.NET classes to retrieve data from a SQL Server database
  2. Convert the retrieved data into business objects of our own class design; classes that could be ported without change to a Web or desktop version of the application
  3. Use LINQ to Objects, both (1) in the binding of data between our business objects and our UI controls and (2) in the definition of our business objects
  4. Place all business objects within a single application data object
  5. Use XML serialization to persist the application data object to the device's object store
  6. Provide data validation within our business objects
  7. Provide change tracking within our business objects
  8. Upload changes to the SQL Server database by examining the business objects

In the end, we will be using LINQ to Objects for data binding, for property definitions, and to help with XML serialization.

Figure 7.7 shows the schematic diagram for this version of the application.

Figure 7.7

Figure 7.7 Sample Application Diagram: LINQ to Objects

If you think this version of the application will require more code than the previous version, you are correct; in fact, it will require significantly more code. This is why there will be a third version later in this chapter, one that attempts to combine the best aspects of the first two in the least amount of code. In the meantime, we need to focus on LINQ to Objects, for the more complex your application becomes, the more you need classes of your own design that encapsulate the business requirements of your application.

However, we cannot begin our discussion of LINQ to Objects without first discussing objects in general. Specifically, we need to discuss business objects, those objects that we design and write to represent the entities of our application—objects such as appointment, customer, product, and so forth—objects that are often referred to as the middle tier.

7.2.2.1 Business Objects

Since our business objects are in the middle tier, data is passing through them on its way between the user interface and the host database. It would be nice, then, if our business objects provided some support for this data movement along with their purely business functionality, such as an invoice class's CalculateOverdueCharge method.

Support for Disconnected Operations

The first area in which a business object can provide support is in data validation. One of the great benefits of properties being defined as two methods, set and get, rather than as a field is that the object can police the values that are being assigned to it, rejecting those that it finds unacceptable by throwing an ArgumentException exception. Again, who better to specify the acceptable amount of money for a withdrawal than the BankAccount class itself?

And by placing the criteria for the property values within the property's set accessor, one can use that class in any type of application—smart device, desktop, Web, or other—and be assured of consistent and uncircumventable data validation. Also, by placing the validation code in the properties, we need not worry about which event handler is the appropriate place to do validation—the TextBox's TextChanged event, the List-View's Validating event, or some other handler—for we will not be doing validation in any event handler. The business object, not the UI tier, is the better place for validation logic.

The second area of business object benefit related to data movement is change tracking. We have already seen this capability in ADO.NET's DataRow class. Each row tracks whether it has been added, modified, or deleted since the data table was last synchronized with the source database. It would be nice if our business objects provided this same state tracking.

At the start of the workday, when a retail driver cradles his smart device, the application downloads data from the server and creates the business objects. Throughout the day, as information is entered, things are added, modified, and deleted. It would be nice if each business object tracked this fact. Then, at the end of the working day, pushing those changes back to the database becomes a matter of noting what changes occurred to what objects and transmitting them to the matching DBMS rows. This is the technique used by ADO.NET's DataAdapter object, which pushed changes from each row in a DataTable to a row in the database by matching the primary key value of the DataRow with the primary key value of the database table's corresponding row.

A third area of potential benefit, related to change tracking, is concurrency support. When our retail driver of the preceding paragraph downloads data from the host to his device, he expects to have pulled "his" information; his customers, his orders, and so forth. When uploading changes, the driver is not expecting that other individuals have modified that information in the host DBMS during the driver's working day. But it could have happened, and the application may need to deal with this possibility. The application must be able to detect that changes have occurred to the data since the data was retrieved and provide up to four possible choices when conflicts are detected: namely, make the driver's change at the host or do not make the change; and notify the driver or do not notify the driver.

Not changing a record because someone else made a change to that record while you were disconnected from the DBMS is called optimistic concurrency, as in you do nothing to prevent others from modifying the data because you are optimistic that they will not do so. Optimistic concurrency means writing an update statement that says the following:

UPDATE TableX
   SET ColA = this,
       ColB = that
 WHERE ColPrimaryKey = PKValue
   AND Other Columns still contain the values that I downloaded.

And therefore, it means remembering the downloaded value, usually referred to as the original value, of a field as the current value is being changed. In the preceding SQL, Other Columns might be as few in number as one, as in the case of a SQL Server TimeStamp column; or as many as all of the downloaded columns. The inclusion of the primary key in the WHERE clause means that one data modification statement must be submitted to the host DBMS for each object whose state has changed, just as a Data-Adapter generates one INSERT, UPDATE, or DELETE statement for each altered row.

One Row, One Object

Each row from each table will be converted into a business object as it reaches our application: one class for employee, one for customer, one for product, one for order, and one for order detail. Figure 7.8 shows each class. If it looks almost identical to the data set diagram shown earlier, it should. What is different between the two figures is the lack of relationships in Figure 7.8. Instead of hard-wired relationships between the classes, the relationships are defined by read-only properties, such as Order.Details and Order.parentCustomer. We will discuss these properties, and the use of LINQ in defining them, in greater detail later in this section; for now, we need to discuss the reason for avoiding hard-wired relationships in our application data.

Figure 7.8

Figure 7.8 The Five Business Objects

Since our data might come from a different source at some future time, we need to be flexible and not tie our business objects to their data source. After all, a customer is a customer regardless of where her information is stored. For this reason, we will write a class that uses ADO.NET to execute the aforementioned stored procedure and process the rows that are returned, turning each into an object of the appropriate class and adding each object to an application data object. By adding every business object, such as the employee object, the objects for that employee's orders, and so on, to a single application data object, we can save all application data to device storage by using XML serialization to store the application data object to a file. For further information, see the XML Serialization section of Chapter 5, Storage.

But perhaps that XML serialization won't be as simple as we first think it will be; things never are. Or more correctly, since our application will benefit from having a single XML-serializable object that holds all of our data, perhaps we had best design that object first.

Since the application's data relates to a single employee, you might think that a single employee object that served as the head of a tree of related objects would be the best design. Unfortunately, this design has two snags.

  1. First, the Employee object would be unserializable because the Employee object would have an Orders property, or a collection of references to Order objects. And each Order object would have a parentEmployee property containing a reference to the Employee object. Thus, the Employee object would contain circular references, and that would make it, as we mentioned in Chapter 5, unserializable.
  2. Second, as we mentioned earlier in this chapter, all customers and all products must be downloaded to the application, even those that currently have no relationship with the employee. Thus, the Employee object would not be connected to all of the other objects needed by the application.

A second design choice would be to have a separate application data object, one that contained dictionaries and lists: a Dictionary containing the one and only Employee object, a Dictionary containing that employee's Orders, a List containing all the Details of those Orders, a Dictionary containing all the Customers, and a Dictionary containing all the Products. Since Details are always retrieved via their parent order and not by their primary key, they can be placed in a List rather than in a Dictionary, thus saving us the trouble of having to convert the Detail's composite primary key into a single-valued dictionary key.

Each business object, such as Order, would contain no references, only its primary key and foreign key values from the database. The primary key values from the database would now be the Dictionary keys as well. There would still be an Employee.Orders property and an Order.parentEmployee property that expose object references, but they would be read-only properties that used LINQ to generate their values on the fly. Since the objects would not actually contain any reference fields, there would be no possibility of circular references. This is the design we will use, as shown in Figure 7.9.

Figure 7.9

Figure 7.9 Structure of the Application Data Object

We name our application data class, as we mentioned earlier, AppData. The code for the dictionaries and list that comprise this object is shown here:

public Dictionary<int, Employee> Employees;
public Dictionary<string, Customer> Customers;
public Dictionary<int, Product> Products;
public Dictionary<int, Order> Orders;
public List<Detail> Details;

As you can see, the application data object is very simple and very functional. It is also not XML-serializable. More specifically, its dictionaries are unserializable.

Several Web sites discuss writing your own XML-serializable dictionary class and provide sample code. We chose not to use them because we did not want to introduce any additional nonbusiness-specific classes, and because we wanted to stay with the standard .NET collection classes.

Rather than give up our application data class design, we will take advantage of the fact that, while instances of the Dictionary class are not XML-serializable, instances of the List class are, in fact, XML-serializable. When the time comes to serialize or deserialize our data, we will simply move each set of Dictionary data to or from a List. Using LINQ, each List can be easily generated from the corresponding Dictionary's Values property by using the ToList operator. And each Dictionary can be generated from the corresponding List via the ToDictionary operator if each object's key, such as OrderId, is a property of the object. As long as the key is contained within the object, you can always use LINQ to generate a Dictionary from a List of the objects.

To perform the serialization of application data to and from a file, we write a class named AppToXml. This class does the following:

  • Contains the application data in five List objects
  • Serializes and deserializes itself to a file
  • Transfers data between its Lists and the application's Dictionarys

Listing 7.8 shows the serialization code from this class.

Listing 7.8. Serialization Code from AppToXml Class

using System;
using System.LINQ;
using System.Collections.Generic;
using System.IO;
using System.Xml.Serialization;
        :
        :
internal static void WriteAppData(string fullPath)
{
   AppToXml otx = new AppToXml();
   AppData oed = AppData.Current;

   otx.Employees = oed.Employees.Values.ToList<Employee>();
   otx.Customers = oed.Customers.Values.ToList<Customer>();
   otx.Products = oed.Products.Values.ToList<Product>();
   otx.Orders = oed.Orders.Values.ToList<Order>();
   otx.Details = oed.Details;

   FileStream fs = new FileStream(fullPath,
                                  FileMode.Create,
                                  FileAccess.Write);
   XmlSerializer xs =
      new XmlSerializer(typeof(AppToXml));
   xs.Serialize(fs, otx);
   fs.Close();
}
        :
        :
internal static void LoadAppData(string fullPath)
{
   FileStream fs = new FileStream(fullPath,
                                  FileMode.Open,
                                  FileAccess.Read);
   XmlSerializer xs =
      new XmlSerializer(typeof(AppToXml));
   AppToXml otx = (AppToXml)xs.Deserialize(fs);
   fs.Close();
   AppData oed = AppData.Current;
   oed.Clear();
   oed.Employees =
      otx.Employees.ToDictionary(empl => empl.EmployeeID);
   oed.Customers =
      otx.Customers.ToDictionary(cust => cust.CustomerID);
   oed.Products =
      otx.Products.ToDictionary(product => product.ProductID);
   oed.Orders =
      otx.Orders.ToDictionary(order => order.OrderID);
   oed.Details = otx.Details;
}

Again, note the use of the => operator. The phrase (empl => empl.EmployeeID) says that the EmployeeID property is to be treated as the function that returns the object's key value. Thus, for each Employee object, a reference to the object will be placed in empl, and the value of empl.EmployeeID will be calculated and then used as the Dictionary key.

So, even with serialization, a subject not directly associated with LINQ, we find that we get help from LINQ's ToList and ToDictionary methods, which enable us to convert lists into dictionaries, and vice versa.

Now that we can move our application data to and from a local file, let us examine the objects that comprise this data more closely, especially the parts that use LINQ to Objects.

7.2.2.2 The Business Objects

There are five business object classes in our application: Employee, Customer, Product, Order, and Detail (each Detail object represents a line item on an order). We will show more code from the Order class than any other simply because it participates in more relationships than any other. And we will be focusing on the use of LINQ within some property definitions and on change tracking. The two subjects are related, as changing a property value can change the object's state. Just as a property's set accessor must validate the value being assigned, it may need to update the object's change state. Other actions may also result in an update to the object's change state. As Table 7.2 shows, these changes in state are not as straightforward as one might first expect.

Table 7.2. State Table for Our Business Objects

Action

Old State

New State

Retrieve from host database

None

Unchanged

Create

None

New

Modify

New

No change

Unchanged or Updated

Updated

Deleted or Moot

Either no change or InvalidOperationException

Delete

New

Moot

Deleted or Moot

Either no change or InvalidOperationException

Unchanged or Updated

Deleted

Moot objects are objects that exist in neither the application nor the host database; they result from a new object being deleted before the application pushes changes to the database, as in "the user changed her mind." Data from Moot objects is never passed to the host. Deleted objects exist in the database but not in the application. They result in a DELETE statement being passed to the database during synchronization.

A New object is one that exists in the application but not on the host. It results in an INSERT statement being passed to the database. Therefore, modifying a New object does not make it an Updated object; it remains a New object. An Updated object is one that is out of sync with the database, and it results in an UPDATE statement being passed to the database.

The state names are our own and are similar to those used by the DataRow class. They are defined in the application as a set of enumerated values:

[Flags()]
public enum ObjectState
{
   Unchanged = 1,
   New = 2,
   Upated = 4,
   Active = 7,    // Unchanged, New, or Updated.
   Deleted = 8,
   Moot = 16,
   NotActive = 24  // Deleted or Moot.
}

To help determine which objects are active or inactive, we wrote a trivial routine to examine an ObjectState value and determine whether it is Active or NotActive:

internal static bool IsActive(ObjectState state)
{
   return (state & ObjectState.Active) != 0;
}

Since change in an object's state is, in part, tied to changing its property values, we will begin our examination of our business object code with properties.

7.2.3 Business Object Properties

The properties of our business objects fall into two general categories: read-write properties that are backed by a private field, such as the Order.OrderDate property; and read-only properties, or properties whose values are generated on the fly rather than being backed by a field. In our application, read-only properties are used to reflect the relationships between objects, such as the Order.Details property, and to expose calculated values, such as Order.NetValue. LINQ code will be used to generate property values in both scenarios.

7.2.3.1 Read-Write Properties

It is the read-write group of properties that needs to validate data and update state. To simplify the coding of both requirements, we write two routines for setting property values: one for ValueType data and one for Strings. The ValueType helper routine is a generic routine that allows the user to specify a value plus optional minimum and maximum values for validation, plus pointers to the current and original value fields. It is shown in Listing 7.9.

Listing 7.9. One Routine for Setting Property Values

internal static void SetValueProperty<T>(
                                string fieldName,
                                T value,
                                T minAllowable,
                                T maxAllowable,
                            ref T currValue,
                            ref T prevValue,
                            ref ObjectState state)
{
   if (  state == ObjectState.Deleted
      || state == ObjectState.Moot)
   {
      throw new InvalidOperationException
         ("A deleted object cannot be modified.");
   }

   if (value != null)
   {
      IComparable icompValue = (IComparable)value;
      if ((icompValue).CompareTo(minAllowable) < 0
         || (icompValue).CompareTo(maxAllowable) > 0)
      {
         throw new ArgumentOutOfRangeException(
            string.Format(
               "{0} must be between {1} and {2}",
               fieldName,
               minAllowable, maxAllowable));
      }
   }

   prevValue = currValue;
   currValue = value;

   if (state == ObjectState.Unchanged)
      state = ObjectState.Updated;
}

The IComparable.CompareTo routine must be used, as there is no generic implementation of ">", "<", or "==".

The String equivalent, obviously, is a nongeneric routine. It uses an optional regular expression parameter for validation rather than minimum and maximum values. Other than that, it bears a strong resemblance to the ValueType setting routine. Our SetStringProperty method appears in Listing 7.10.

Listing 7.10. A Second Routine for Setting Strings in Read-Write Property Values

internal static void SetStringProperty(string fieldName,
                                       string value,
                                       string regex,
                                   ref string currValue,
                                   ref string prevValue,
                                   ref ObjectState state)
{
         :
         :
   if (!string.IsNullOrEmpty(regex)
    && !new Regex(regex).IsMatch(value))
   {
      throw new ArgumentException(
         string.Format(
            "{0} must match this pattern:  {1}",
            fieldName, regex));
   }
         :
         :
}

The two regular expressions are used to validate customer IDs and employee names. The latter are restricted to the U.S. English characters:

internal static string
   regexpCustomerID = @"^([A-Z]{5})$",
   regexpUSName =
         @"^[a-zA-Z]+(([\ \,\.\-][a-zA-Z])?[a-zA-Z]*)*$";

We are indebted to www.RegExpLib.com and one of its contributors, Hayk A, for providing the source of these expressions. Setting a read-write property value is now a matter of calling the appropriate helper routine, as illustrated by the code excerpt from the Order class shown in Listing 7.11.

Listing 7.11. Calling Our Helper Routine to Set CustomerID Values

private string _CustomerID, _origionalCustomerID;
public string CustomerID
{
   get
   {
      return _CustomerID;
   }
   set
   {
      OrderEntryData.SetStringProperty("CustomerID",
                              value.Trim(),
                              OrderEntryData.regexpCustomerID,
                          ref this._CustomerID,
                          ref this._origionalCustomerID,
                          ref this.objectState);
   }
}


private DateTime _OrderDate, _origionalOrderDate;
public DateTime OrderDate
{
   get
   {
      return _OrderDate;
   }
   set
   {
      OrderEntryData.SetValueProperty("OrderDate",
                              value,
                              DateTime.Today.AddYears(-20),
                              DateTime.Today,
                          ref this._OrderDate,
                          ref this._origionalOrderDate,
                          ref this.objectState);
   }
}

We suggest you keep two things in mind regarding property value validation. First, data that is pulled from the database will be validated as the objects containing that data are created, and that data must be able to pass validation. For instance, our allowable OrderDate range might seem a little generous, but the Northwind database is well more than ten years old with many of its orders dating back to the mid-1990s. Those orders must successfully download into our application, hence the resulting looseness of our validation criteria. If different validation rules are to apply for new data vis-à-vis downloaded data, the validation routine will need the ability to differentiate between the two.

Second, few things make a developer feel more foolish than providing a default value that fails validation. It's an easy mistake to make, such as requiring a transaction amount to be a positive measurable amount and then supplying a default value of $0.00.

7.2.3.2 Read-Only Properties

Our second set of properties, the read-only properties, provides references to related objects and calculated values. For instance, Order.NetValue uses LINQ to iterate through the Details dictionary, selecting the details of a specific order and returning the sum of their values, whereas Order.parentCustomer returns a reference to the order's customer object, an object that is located in the Customers dictionary within our application data object. Customer.Orders returns not a single reference but rather a List of all of the customer's order objects from the Orders dictionary, using LINQ to do so.

Remember from an earlier discussion that our business objects do not store references to other objects, for doing so would lead to unserializable objects. Rather, they use the object's primary key and foreign key value properties, such as CustomerId, to obtain the related object references from the Dictionarys.

The Order class has four read-only properties: parentEmployee, parentCustomer, Details, and NetValue. Listing 7.12 shows the three that are related to exposing object references.

Listing 7.12. Accessors for Three Read-Only Properties

[XmlIgnore()]
public Customer parentCustomer
{
   get
   {
      return
         OrderEntryData.Current.Customers[this.CustomerID];
   }
}

[XmlIgnore()]
public Employee parentEmployee
{
   get
   {
      return
         OrderEntryData.Current.Employees[this.EmployeeID];
   }
}

[XmlIgnore()]
public List<Detail> Details
{
   get
   {
      return
         (OrderEntryData.Current.Details
            .Where(detail =>
               OrderEntryData.IsActive(detail.objectState))
            .Where(detail =>
               detail.OrderID == this.OrderID))
            .ToList();
   }
}

Again, a comment on alternative syntax: If you prefer the query expression syntax, you could write the Details' get accessor as shown here:

Return (from d in OrderEntryData.Current.Details
where OrderEntryData.IsActive(d.objectState) &&
      d.OrderID == this.OrderID
select d)
.ToList();

The XmlIgnore attribute that is applied to each property is necessary to prevent the property from serializing. We want our object's read-write properties to serialize, for they contain actual data. But our read-only reference-exposing properties are, as mentioned earlier, circular in nature. XML-serializing them is something that we must avoid.

The two parent... properties are so simple that they do not need any LINQ code. The LINQ code in the Details property accesses the Details dictionary in the application data object, retrieving all active details for this order.

LINQ code is also used in calculating the read-only NetValue property of the order, summing the net values of the order's details and returning the total, as shown here:

return
   this.Details
      .Where(od => (OrderEntryData.IsActive(od.objectState)))
      .Sum(detail => detail.NetValue);

Note that this is an example of a LINQ expression that returns a single value, not a collection of objects.

Properties comprise most of the code contained within our business objects, with a few constructors and default value literals (neither of which require any LINQ code) thrown in.

LINQ also appears in our UI code. The most complex LINQ statement in our application was the one, presented at the start of this section and repeated in Listing 7.13, that displays information in a combo box. It is nearly identical to the one used in the LINQ to Datasets example except that it accesses a dictionary rather than a data table and uses a where clause to filter out any inactive orders.

Listing 7.13. LINQ in Support of User Interface Code

cbxOrders.DisplayMember = "Text";
cbxOrders.ValueMember = "Id";
cbxOrders.DataSource =
(
   employee.Orders
      .Where(order =>
         (OrderEntryData.IsActive(order.objectState)))
      .OrderBy(active =>
         active.parentCustomer.CompanyName)
         .ThenByDescending(active => active.NetValue)
         .ThenByDescending(active => active.OrderDate)
      .Select(sorted =>
         new
         {
            Id = sorted.OrderID,
            Text =
                   sorted.parentCustomer.CustomerID
                 + " - "
                 + sorted.NetValue.ToString("c")
                           .PadLeft(9).Substring(0, 9)
                 + " - "
                 + sorted.OrderDate
                           .ToString("dd-MMM-yy")
         })
)
.ToList();

The code, in summary, does the following:

  1. Extracts all the active orders from the Orders read-only property of the Employee object
  2. Sorts them into descending order date within descending net value within customer sequence
  3. Converts each order into an object of an anonymous class containing

    1. An order ID property named Id
    2. A new property, named Text, that is the concatenation of the customer ID / net value / order date property
  4. Converts that collection into a List
  5. Assigns that List to the data source property of a ComboBox, specifying that the Id property of the newly created objects will be treated as the key value, and that the Text property value will be displayed in the ComboBox

The results of this code are shown in Figure 7.10. As we would expect, it looks identical to Figure 7.5, for although we are using LINQ against a generic collection instead of a data table, the LINQ expression is essentially the same.

Figure 7.10

Figure 7.10 Display of LINQ Assembled Data

As before, had we wanted to sort on a property of the newly created anonymous objects, such as the Id or Text property, our sort would need to occur after the anonymous objects were constructed, and the code would have resembled the code shown in Listing 7.14.

Listing 7.14. Sorting on Anonymous Objects

cbxOrders.DataSource =
   (Program.appData.Employees[testEmployeeID].Orders
      .Where(order =>
         (DataOrderEntry.IsActive(order.objectState)))
      .Select(sorted =>
         new
         {
            Id = sorted.OrderID,
            Text = sorted.parentCustomer.CustomerID
                 + " - "
                 + sorted.NetValue.ToString("c")
                      .PadRight(9).Substring(0, 9)
                 + " - "
                 + sorted.OrderDate.ToString("dd-MMM-yy")
         })
      .OrderBy(item => item.Text))
      .ToList();

It is interesting to note that the source collection for the LINQ queries shown in Listings 7.13 and 7.14, the Employee object's Orders property, is itself a LINQ expression. In that regard, it is similar to the Order object's Details property shown in Listing 7.12. Thus, the code shown in Listing 7.14 is an example of a LINQ expression whose complete definition is divided between two separate C# statements.

Even the code used to submit changes back to the remote database benefits from LINQ, if only slightly. For example, the code that loops through all the orders looking for deleted ones and then sets a parameter value and submits the "execute delete stored procedure" command, goes from

foreach (Order order in context.Orders.Values)
{
   if (order.objectState == ObjectState.Deleted)
   {
      cmnd.Parameters.AddWithValue("@OrderID",
                                    order.OrderID);
      cmnd.ExecuteNonQuery();
   }
}

to

foreach (Order order in context.Orders.Values
            .Where(order =>
               order.objectState == ObjectState.Deleted))
{
   cmnd.Parameters.AddWithValue("@OrderID",
                                 order.OrderID);
   cmnd.ExecuteNonQuery();
}

This code is the last LINQ code in this version of our application.

Throughout this section, we used LINQ to Objects to access collections of objects; filtering, sorting, aggregating, converting, and performing other operations, all within a single statement—occasionally a rather long statement but always a single statement. As we wrote these statements, we received IntelliSense help, allowing us to select our operations, see the available properties, and invoke .NET methods or our own methods as we went. In all, we used LINQ to define properties, bind data, transform objects in preparation for XML serialization, and locate unsynchronized data.

Business objects made our application more functional, modular, and representative of the business; and although LINQ to Objects made much of that code easier to write, we still needed to write significantly more code in the LINQ to Objects version than we did in the LINQ to Datasets version, especially in the area of change tracking and data synchronization. What makes the writing of this additional code even more disconcerting is the fact that we know this code has already been written by others.

Whoever designed and authored the System.Data, and related namespace, classes wrote change tracking and data synchronization logic, for we can see it in the DataRow and DataAdapter classes. Whoever wrote the DataContext class for LINQ to SQL on the desktop wrote change tracking and data synchronization logic. We would like to avoid reinventing the wheel and instead have an application that provides the benefits of business objects with already proven change tracking and data synchronization capability, thus producing the most functional application while writing the smallest amount of code. And that leads us to the hybrid version.

7.2.4 The Hybrid Version

We begin with the realization that each of our business objects was created from a row in the database and that each object's data consisted of individual fields that were exposed as properties. Why, then, not load the data into a data set and use the column values of the rows as the backing fields for the object's read-write properties?

In this scenario, each object would contain the reference to its corresponding data row and nothing more. To put it another way, the object would be, in effect, data-bound to the data row. Any value assigned to a property of the object would be stored in the matching field of the data row, from whence it would be retrieved whenever the property value was accessed. No data would be duplicated, as the business objects would be holding a reference to the data row, not a copy of data. And the data rows would provide change tracking on behalf of the objects.

In addition, the application's data could be written to a file by serializing the data set rather than the application's data object. The application's data object, containing its collections of customers, orders, and so on, would still be needed, for we want the benefit of an object's read-only properties, such as Order.Details and Order.parentCustomer, and the data validation benefit that comes with the read-write properties. But this new application data object would no longer need to be serializable. Having an application data object that does not need to be serialized provides greater design flexibility and requires less code.

In this scenario, our business objects would provide data binding for the UI and the source of all business logic. The data set would provide serialization of application data, change tracking, and the uploading of data changes back to the remote data source, thus achieving our original application goals, shown in the following list, while requiring the least amount of programming on our part.

  1. Retrieve all of the employee's orders from the host SQL Server.
  2. Add, delete, and modify orders.
  3. Save/restore all application data to a local file.
  4. Upload all entered information to the host SQL Server.

Figure 7.11 shows the updated schematic diagram, representing this hybrid version of our application.

Figure 7.11

Figure 7.11 Sample Application Diagram: Hybrid Version

So, let us now examine the code reductions in this hybrid version of our application. The data would be read into a data set, saved to a file, and returned to the source database, using the same code that was in the LINQ to Datasets version. The definition of the business objects and the application data object remains mostly the same. The constructors of the business objects change, as they are now created from data rows rather than from a data reader, and they store a reference to the row rather than its data. For instance, the Order constructor for creating an Order from a data row is as follows:

public Order(DataRow rowThis)
{
   this.rowThis = rowThis;
}

And the constructor creating a new order, which must create a new data row and then fill it with default values, is as follows:

public Order()
{
   DataTable myTable =
      AppData.Current.dsetEmployee.Tables["Orders"];
   rowThis = myTable.NewRow();
   this.OrderID =
      AppData.Current.Orders.Values
         .Max(order => order.OrderID) + 1;
   this.EmployeeID = AppData.Current.EmployeeID;
   this.CustomerID = string.Empty;
   this.OrderDate = Order.defaultOrderDate;
   this.RequiredDate = Order.defaultRequiredDate;
   this.ShippedDate = Order.defaultShippedDate;
}

And the OrderDate read-write property, for instance, backed by the matching field in the data row, becomes the following:

public DateTime OrderDate
{
   get
   {
      return (DateTime)rowThis["OrderDate"];
   }
   set
   {
      AppDataUtil.ValidateValueProperty(
                           "OrderDate",
                           value,
                           DateTime.Today.AddYears(-100),
                           DateTime.Today);
      rowThis["OrderDate"] = value;
   }
}

The read-only properties of the Order class, which use LINQ to select information from the application's collections, such as Order.NetValue, remain unchanged, as shown here:

public decimal NetValue
{
   get
   {
      return this.Details.Sum(detail => detail.NetValue);
   }
}

All serialization code, and all change tracking/data source update code, is gone, replaced by the capabilities inherent in the data set, data table, and data adapter classes.

Certainly, we have been able to achieve the best of both worlds: ADO.NET for retrieving, tracking, and persisting data, and business objects for validation, encapsulation, and use of the user interface with that data. All we need now is a nice, flexible way to send, receive, and store this information as XML to, from, and on our device.

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